When it comes to AI budgeting, less is more, as long as you are strategic
Whether we like it or not, there is incredible pressure on companies to adopt AI. That pressure is only increasing as AI spending is expected to grow by almost 30% over the next four years. Still, questions remain about what and how much AI can actually do. As we enter budget season, these pressures have IT departments in every sector scratching their heads trying to figure out how much to allocate to AI pilots. If you spend too little, the competition can develop an insurmountable advantage. If you spend too much, you may find that there isn’t enough ROI.
The reality is: AI needs a plan. With the right strategy, you can kick-start your projects by investing just a fraction of your budget. Well-executed AI initiatives have the potential to not only pay for themselves, but also generate significant returns. By setting a clear roadmap for adoption, you’ll be ahead of the curve and position yourself as a leader in the AI game.
Managing Director of Intelligent Automation, AI & Digital Services at Alliant.
Even 1% of your budget can be done right
Let’s get this out of the way: Spending more on AI doesn’t make you an AI leader. Wedbush published a report showing that 1% of total revenue (about 8-10% of IT budgets) at major tech companies would be spent on AI. Meanwhile, a survey of CIOs found that 61% find it extremely challenging to prove ROI on their technology investments, while 42% do not expect a positive ROI from AI projects in the coming year.
Think about that for a moment: how much technology debt does your IT department already have due to projects that yield no or even negative returns. Now you face the added pressure of relying on a new solution. The critical question is how to introduce AI within the constraints of your available budget while demonstrating an ROI that drives widespread adoption and does not contribute to previous failures.
The key is to start small: initiating pilot projects with a well-planned strategy rather than a comprehensive infrastructure renovation. This approach gives your team the necessary time to transition and adapt, while providing the flexibility for iterative improvements. You’ll be given room for improvisation until you find a solution that works best for your business and see the impact in terms of revenue. By focusing on specific, manageable projects, you can gather valuable data and insights, refine your approach, and gradually scale your AI initiatives.
How do you do it? Here are some guiding principles that I believe will help you get the most out of your AI investment.
• Conduct an “AI Discovery.”
The first step is to consciously define and choose your first wave of AI pilots. There are people inside and outside your organization with a ‘great’ AI idea. If you chase them all, you’ll end up with a budget you can’t justify. On the other hand, if you focus only on the ideas that the loudest voices in the room suggest (or the highest-titled voice), you’re likely to miss the ideas that are likely to have the biggest impact.
We often start with an AI Discovery process where all ideas are put on the table and each idea is objectively scored on a 12-point rubric based on technology suitability, complexity and ROI.
During a recent AI Discovery session with a CPA firm, the tax department wanted to automate tax return preparation, while the accounts receivable team sought to streamline payment processing. The goal behind both was to save more time. However, by assessing these ideas in terms of project scale, complexity, potential ROI, strategic alignment and feasibility, the company decided to prioritize the accounts receivable project.
AI Discovery not only helps select the most promising AI projects, but also ensures that your initial investments are targeted and effective. It allows you to focus your resources on initiatives that are most likely to deliver measurable benefits, increasing the likelihood of a positive ROI.
• Plan and prioritize self-financing transformations
Once you’ve conducted an AI Discovery and identified the most promising pilots, the next step is to focus on initiatives that are less complex but offer faster turnaround in terms of ROI. By starting with these types of AI pilots, you can create a self-financing transformation process that not only justifies the initial investment, but also generates the momentum needed to fund subsequent projects.
By choosing AI projects that are easier to implement and can quickly demonstrate tangible benefits, you can build a strong business case for further investment. These early successes can serve as proof points and demonstrate the potential of AI to drive meaningful improvements and efficiencies within your organization. For example, automating routine tasks or improving customer service through AI-powered chatbots are examples of low-complexity projects that can deliver quick wins.
Take the case of the CPA firm I mentioned. Through AI Discovery, we identified automating their accounts receivable process as an effective first project, quickly boosting their finances. This success allowed them to automate customer document requests, saving 15% on tax return preparation time (which was the original project proposed by the tax team).
As with the CPA firm, you can invest the revenue or cost savings from pilot projects into more complex and ambitious AI initiatives. This approach minimizes financial risk and ensures that every step in your AI journey is backed by proven success. It also helps gain trust and buy-in from stakeholders as they can see the direct impact of AI on the bottom line.
• Balance pilot projects with comprehensive AI transformation
As you focus on launching pilot projects, don’t lose sight of the bigger picture. Ultimately, the greatest ROI will come from company-wide AI initiatives. To achieve this, your entire organization must be AI-ready. This means fostering a culture open to innovation, investing in training and development, and ensuring your infrastructure can support broader AI applications.
Moreover, you should keep in mind that not all pilot projects will succeed. That’s why you should never put all your AI eggs in one basket. By spreading your AI investments across multiple departments, such as finance, customer service, and operations, you can gather a wide range of insights that can help you mitigate risk and identify the most impactful use cases.
Launching multiple AI pilots across different departments will also accelerate your organization’s readiness for a complete AI transformation. Each successful pilot not only delivers immediate benefits, but also lays the foundation for larger, more integrated AI projects. This approach ensures that your organization continuously learns and adapts, making it more agile and better prepared for future challenges.
The true currency of AI leadership
AI has presented us with an enormous challenge, behind which lies an unprecedented opportunity for growth and innovation. What is clear is that success in the AI race is not determined by the size of your budget, but by the depth of your strategic vision. The real leaders in this area will be those who can artfully balance innovation with fiscal responsibility, deploying small, strategic investments to catalyze transformative change. In this new paradigm, the most successful companies will not just adopt AI – they will redefine how AI adoption itself is approached, setting new standards for efficiency, creativity and return on investment.
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